TRAST, Preventive Measures for Real-World Reliability Dec. 16, 2021, 6pm PST
TRAST, Preventive Measures for Real-World Reliability
by Dr. Xiaoyuan Fan, Pacific Northwest National Laboratory (PNNL)
When the power grid is disrupted – by an outage, a cyberattack, a natural disaster, or an unexpected imbalance of supply and demand – grid operators utilize Remedial Action Schemes (RAS) as the last line of defense to maintain grid reliability and prevent broader, cascading events. RAS represents one of the core resilience components of the electric power system and is also one unique example of the IT/OT technology fusion in grid modernization and digitalization.
In partnership with PacifiCorp and Idaho Power, a Pacific Northwest National Laboratory (PNNL) research team led by Dr. Xiaoyuan Fan has developed Transformative Remedial Action Scheme Tool (TRAST). The patented technology automates the process of identifying and evaluating RAS used by electric utilities to plan for specific contingencies and emergencies. TRAST uses a novel approach to automatically generate use cases, bringing in advanced statistical data analysis tools, and using machine learning algorithms to analyze, validate, and help create RAS plans. PNNL’s parallel computing platform and Microsoft cloud environment are utilized for steady state and dynamic simulations under massive contingencies and operating conditions. More realistic settings of RAS systems in the U.S. Western Interconnection can make the grid more reliable and resilient.
Date and Time
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- Date: 16 Dec 2021
- Time: 06:00 PM to 07:30 PM
- All times are (GMT-08:00) US/Pacific
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- Co-sponsored by Chris Gunning, cgunning@ieee.org, Boise Computer Society chapter chair
- Starts 08 December 2021 02:43 PM
- Ends 16 December 2021 05:45 PM
- All times are (GMT-08:00) US/Pacific
- No Admission Charge
Speakers
Dr. Xiaoyuan Fan
TRAST, Preventive Measures for Real-World Reliability
Dr. Xiaoyuan Fan of Pacific Northwest National Laboratory (PNNL)
Biography:
Dr. Xiaoyuan Fan of Pacific Northwest National Laboratory (PNNL)
Xiaoyuan Fan is currently a senior research engineer with Pacific Northwest National Laboratory (PNNL) located in Richland, Washington. Serving as a project manager, PI/co-PI and key contributor, Xiaoyuan has been managing and supporting multiple research projects funded by the U.S. Department of Energy, Department of State, Department of Homeland Security, ARPA-E, Bonneville Power Administration and other industrial collaborators. His research interests focus on data analytics for power system reliability, wireless communication, multi-discipline resilience analysis, and high-performance computing. Xiaoyuan is a Senior Member of IEEE and serves as a volunteer reviewer of 20+ top-level journals and conferences in power systems and signal processing. He also served as career advisor in 2018 IEEE PES General Meeting Student Job fair and vice president of IEEE student chapter at University of Wyoming from 2013 to 2015. Xiaoyuan is the recipient of a 2021 Federal Laboratory Consortium for Technology Transfer Award, and three Energy and Environment Directorate Outstanding Performance Awards. He received the Ph.D. degree in electrical engineering from the University of Wyoming, Laramie, WY, and M.S. and B.S. degrees in electrical engineering from Huazhong University of Sciences & Technology, Wuhan, China, respectively.
Email: Xiaoyuan.fan@pnnl.gov
Agenda
Dec. 16, 2021 7pm MST (9pm EST, 6pm PST)
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